1. Comparison of Evolutionary Techniques

2. Motivation EAs are general problem solvers EAs are themselves problems EAs should be simpler to apply to new problems

3. Local Mating Pick a location, L Take a random walk from L, for each parent Generate a new child at L

4. Local Survival All sites, including L, are occupied Each offspring must displace some individual, normally at L, or die

5. Complexity Analysis Rank-based: O((m + l) * log(m + l)) – sorting dominates Fitness-proportional: O(m + l) – linear, but generally poor results Grid: O(l) – linear, and independent of m! 1-2 orders of magnitude faster than rank- based!

6. Ackley Function

7. Parallelization Divide the population along each dimension of the grid Exchange information only upon need Asynchronous execution No compromises necessary

8. Delta-Entropy Fitness Holes Define an entropy function Rank the population normally Calculate incremental entropy Randomly use in place of fitness

9. Floating-point Entropy Given alleles {x 0 …x n-1 } DH(i) = nearest neighbor to x i in {x 0 …x i-1 } Disfavors clumps of alleles Inhibits rampant breeding

10. Complexity Analysis O((m + l)* log(m + l) * dim) for sorting each set of alleles ~1 order of magnitude slower

11. Ackley Function